Literature DB >> 19747026

Suboptimal identification of obesity by family physicians.

Osnat C Melamed1, Sasson Nakar, Shlomo Vinker.   

Abstract

OBJECTIVES: To examine how family physicians identify and document obesity. STUDY
DESIGN: Prospective cross-sectional study of 289 patients in 7 family practice clinics of Clalit Health Services in Israel.
METHODS: Two hundred eighty-nine patients from 7 family practice clinics had their body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]) determined by the study staff and subsequently compared with the data retrieved from the family practices' database regarding physicians' BMI documentation and obesity diagnosis. Demographic variables, comorbidities, and medication use were also extracted. Multivariate odds ratios (ORs) and 95% confidence intervals (CIs) were obtained to determine the predictors of BMI documentation.
RESULTS: Seventy-eight of 289 patients (27.0%) were obese (BMI, > or =30.0), and 126 (43.6%) were overweight (BMI range, 25.0 to < or =29.9). Body mass index was documented in 39 of 78 obese patients (50.0%) and in 49 of 126 overweight patients (38.9%) (P <.001). Diagnosis of obesity was recorded in 19 of 78 obese patients (24.4%). Older patients (OR, 2.77; 95% CI, 1.39-5.49) and obese patients (OR, 2.04; 95% CI, 1.04-3.99) were more likely to have their weight and height measured and BMI calculated by their physician. Patients with comorbid conditions such as diabetes mellitus (OR, 4.35; 95% CI, 2.20-8.62) and hypertension (OR, 3.20; 95% CI, 1.71-5.99) and patients taking chronic medications (OR, 3.44; 95% CI, 1.20-9.83) were also more likely to have their BMI documented.
CONCLUSIONS: Family physicians failed to identify most obese and overweight patients, as seen by lack of BMI documentation and concordant diagnoses in the medical problem list. Determination of BMI by physicians in family practice is of utmost importance, and its incorporation into medical care should be optimized.

Entities:  

Mesh:

Year:  2009        PMID: 19747026

Source DB:  PubMed          Journal:  Am J Manag Care        ISSN: 1088-0224            Impact factor:   2.229


  10 in total

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2.  A cross-sectional study examining Australian general practitioners' identification of overweight and obese patients.

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4.  Factors Associated with the Accurate Diagnosis of Obesity.

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Journal:  J Community Health       Date:  2016-12

5.  Multimorbidity and weight loss in obese primary care patients: longitudinal study based on electronic healthcare records.

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Review 7.  Overweight but unseen: a review of the underestimation of weight status and a visual normalization theory.

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Journal:  Obes Rev       Date:  2017-07-21       Impact factor: 9.213

8.  Childhood obesity diagnosis and management remains a challenge despite the use of electronic health records: A retrospective study.

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Journal:  Health Sci Rep       Date:  2022-08-08

9.  Documentation of body mass index and control of associated risk factors in a large primary care network.

Authors:  Stephanie A Rose; Alexander Turchin; Richard W Grant; James B Meigs
Journal:  BMC Health Serv Res       Date:  2009-12-16       Impact factor: 2.655

10.  Effect of modified physiology laboratory sessions on the awareness and knowledge of obesity of health-related university students.

Authors:  Talay Yar; Basil A Alshaikh; Nazish Rafique; Ahmed A Alsunni
Journal:  J Family Community Med       Date:  2020-06-03
  10 in total

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